Quantitative Research Methods
Explore research methods that rely on numerical data and statistical analysis. Learn about surveys, experiments, and correlational studies to test hypotheses and identify patterns.
58 courses
Learn to manage datasets, perform statistical tests, and create professional visualizations using R and RStudio for reproducible research.
Develop the skills to design rigorous studies and analyze social data using R, focusing on research integrity and clear statistical interpretation.
Learn to design robust social science studies, collect high-quality data, and apply ethical research practices to ensure scientific integrity and credibility.
Master the process of designing professional surveys, gathering reliable data, and performing statistical analysis to uncover actionable insights.
Learn how to identify the right data sources, translate business questions into measurable metrics, and design structured data collection plans for reliable analysis.
Master the fundamentals of survey design, data collection, and statistical analysis to drive business growth and understand customer behavior.
Understand how different survey modes and design decisions impact data quality and research outcomes across digital and traditional channels.
Learn to design, execute, and interpret psychological studies using foundational quantitative techniques and modern research standards.
Learn how to design, implement, and analyze reliable quantitative assessments to measure student progress and drive data-backed educational decisions.
Develop the skills to design informative empirical studies by learning how to frame better questions and improve research practices for more reliable results.
Master the principles of data selection to build representative samples from populations, social networks, and administrative databases for reliable analysis.
Learn to transform complex ideas like trust or health into reliable quantitative variables for data analysis and research.
Learn to design and analyze multifactor experiments using ANOVA to optimize processes in engineering, science, and business.
Master the experimental and statistical tools needed to design rigorous evaluations and measure the real-world effects of development programs.
Master the essentials of survey weights, regression modeling, and record linkage in R to accurately combine and analyze complex datasets.
Learn to formulate hypotheses, design robust studies, analyze data using modern statistical methods, and document your findings in a structured scientific report.
Learn how to design scientific surveys, collect reliable social data, and analyze human behavior to make evidence-based decisions in social science and policy.
Master the analysis of complex experimental structures to account for random variability, hierarchical factors, and practical constraints in data collection.
Gain a foundational understanding of multilevel modeling concepts and apply them to analyze hierarchical data using R.
Develop practical skills in quantitative data analysis using Excel and R to extract meaningful insights from your datasets.
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